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RelationGAN

Source Code for Our Paper "When Relation Networks meet GANs: Relation GANs with Triplet Loss"

Requirements:

  • python3
  • pytorch
  • torchvision
  • numpy
  • scipy
  • tensorflow-gpu

Introduction

We provide PyTorch implementations for Relation GAN and some measuring tools.

This code include:

GAN loss name FID(Cifar10)
WGAN-GP wgangp 63.7±0.11
LS_GAN ls_gan 14.9±0.11
vanilla GAN sgan 26.4±0.16
Relativistic_GAN rele 24.1±0.19
Our relu_mean 13.5±0.080

Measuring tools

Frechet Inception Distance(https://github.com/mseitzer/pytorch-fid) Inception Score (https://github.com/google/compare_gan) Kernel Inception distance (https://github.com/google/compare_gan) Multi-scale Structural Similarity for Image Quality (https://github.com/google/compare_gan)

All gan loss function is in 'model' file folder.

In order to evaluate all model in a generally recognized method.We use both tensorflow model and pytorch model to get final result.

Our pytorch inceptionv3 model can be download here (https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth)

Our tensorflow inceptionv3 model can be download here (http://download.tensorflow.org/models/frozen_inception_v1_2015_12_05.tar.gz)

How to use?

git clone 
cd Final_RelationGAN\Final\

#train gan model with relation loss and 64 resolution.
python train.py --name Relation --which_loss mean_relu --dataroot path_to_img --gpu_id 1 --resize_or_crop resize_and_crop --which_step lateset --loadSize 64 --which_model_netG basic_64 --which_model_netD relation_64 
#test gan model with relation loss and 64 resolution.
python test.py --name Relation --which_loss mean_relu --result_path path_to_save_reult --gpu_id 1 --which_step lateset  --loadSize 64 --which_model_netG basic_64 --which_model_netD relation_64
#get FID SCORE with Inception-v3 model trained by pytorch.
python FID_Measure.py --name Relation --which_loss mean_relu --dataroot path_to_img --gpu_id 1 --resize_or_crop resize_and_crop  --loadSize 64 --which_model_netG basic_64 --which_model_netD relation_64
#get IS,KID,MS_SSIM with Inception-v3 model trained by tensorflow.
python IS_Score_Tensorflow.py --name Relation --which_loss mean_relu --dataroot path_to_img --gpu_id 1 --resize_or_crop resize_and_crop --which_step lateset  --loadSize 64 --which_model_netG basic_64 --which_model_netD relation_64

Acknowledgments

Our code is based on pytorch-CycleGAN-and-pix2pix(https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)